Solving the New Equation for Advanced Analytics Talent

Over the past 30 years the age of peak earnings has been almost constant in the US (40-50) but had a major decline in the PRC from ~ 55 to 35. China has seen lower returns to human capital then the US. Three core findings, “….In this paper, we first document stark differences in the cross-sectional age-earnings profiles between the U.S. and China, the two largest economies in the world, during the past thirty years. We find that, first, the peak age in cross-sectional age-earnings profiles, which we refer to as the “golden age,” stayed almost constant at around45-50years old in the U.S., but decreased sharply from55to around35years old in China; second,the age-specific real earnings grew drastically in China, but stayed almost stagnant in the U.S.; andthird, the cross-sectional and life-cycle age-earnings profiles looked remarkably similar in the U.S., but differed substantially in China….”

Hanming Fang and Xincheng Qiu, "“Golden Ages”: A Tale of the Labor Markets in China and the United States," National Bureau Of Economic Research, November 2021, https://www.nber.org/papers/w29523

Korea’s path“…Is this a realistic prediction? Only history will tell for sure, but interestingly, Figure11shows that such a pattern of increasing “golden ages” actually happened in Korea during the past ten years, using data from the Korean Labor and Income Panel Study (KLIPS). Korea experienced its fastest growth during the1960s to1990s. After that, it began to slowdown. Appendix Figure A.6depicts the decomposition for Korea, together with the decomposition for U.S. and China. It is worth noting that the cohort effects are particularly large from cohort1945to cohort1960, but starts to decelerate afterwards. This is consistent with our explanation of the race between inter-cohort productivity growth and returns to experience. As inter-cohort productivity growth starts to give its way to experience in Korea, the “golden age” comes back to older ages, as in our hypothetical scenario in Figure10…”

Potential implications, “…We also use the inferred components, particularly the series of the quantities of human capital, to revisit several important and classical applications in macroeconomics and labor economics, including the growth accounting and the estimation of the TFP growth, and the college wage premium and the skill-biased technical change. We find that once we adjust for the changes in the quantities of human capital, the estimated contribution of the TFP to GDP per capita growth is smaller than the previous estimates in the literature. We also find that the skill-biased technical change played an important role in the rising college premium to ensure that the relative price of college human capital does not drop as much as it would otherwise do when there is a large increase in the quantity of college human capital. A simple simulation exercise using our framework also suggests that, as the Chinese economy slows down to a “new normal” growth rate similar to that in the U.S., the golden ages of the cross-sectional age-earnings profile in China will start to increase to older ages, similar to what has happened in Korea in the last ten years….”

Theory, “…To explain these striking differences, we propose and empirically implement a unified decomposition framework to infer from the repeated cross-sectional earnings data the life-cycle human capital accumulation (the experience effect), the inter-cohort productivity growth (the cohort effect), and the human capital price changes over time (the time effect), under an identifying assumption that the growth of the experience effect stops at the end of one’s working career. The decomposition suggests that China has experienced a much larger inter-cohort productivity growth and higher increase in the rental price to human capital compared to the U.S.; but the return to experience is higher in the U.S….”

Datapoint suggesting underlying talent might be constrained, “…The contributions of relative labor supply, relative human capital per worker, and skill-biased technical change to the evolution of relative human capital prices are depicted in Figure9. Itshows clearly that in both U.S. and China, the relative quantity of college human capital grows rapidly, which would have led to sharp declines in the price of college human capital relative to non-college human capital. Due to skill-biased technical changes, the relative price of collegehuman capital did not decline even more in the U.S. and actually increased in China in the last thirty years….”

“…For example, college and high school graduates may possess different types of skills that are not perfect substitutes. To do so, we perform the decomposition as discussed in Section4separately for college workers and high school workers. College and high school workers are allowed to have different paths of life-cycle human capital growth, different inter-cohort human capital growth, and different time series of human capital price changes. The only restriction is that for both college workers and high school workers, there is no additional skill accumulation from experience in the last two experience bins towards the end of working life. Since our imputation of potential experience assumes that college graduates start to gain experience from22years old and high school graduates start to gain experience from18years old, effectively it is assumed that college graduates do not have additional returns to experience in52-61years old and high school graduates in48-57years old. This is largely overlapped with the “flat spot” proposed by Bowlus and Robinson (2012). After detailed investigation of the U.S. data, they conclude that a reasonable choice for the flat spot of the experience effect is around50-59for college graduates and46-55for high school graduates The results are presented in Figure7. First, within an education group, the returns to experience are still higher in the U.S. than in China. Within a country, the experience effects are larger for college workers than high school workers. This is consistent with findings documented by the previous literature that life-cycle wage growth tends to be faster for workers with more education (see Bagger et al., 2014, for example). The difference between the two education groups in their experience effect profiles, however, is much smaller compared to the difference in the cohort effects that we are turning to….”

Controlling For Education The Returns To Experience Are Still Higher In US Relative TO PRC

“…We present the contribution of each source — physical capital per worker, human capital per worker, and the residual — to the growth of GDP per worker in Figure5. We find that all three sources contribute almost equally to the U.S. growth, with the contribution of human capital slightly exceeding the other two sources. The picture is quite different in China. Although the absolute level of the growth in human capital is larger in China than in the U.S., the relative contribution of human capital turns out be the least important to China’s growth. But this is merely a result of an even faster speed at which the physical capital and TFP grow in China. In fact, physical capital is responsible for almost60% of the growth in GDP per worker, and TFP for almost another30% in China….”

Chinese GDP Per Worker Driven By Physical Investment, Not Human Capital Or TFP

“…Conceptually, across-sectionalage-earnings profile, which summarizes earnings of workers of different ages at a given point of time, is a different notion to thelife-cycleearnings profile, which tracks the earnings of a typical person over his life course. Thus one should not expect the crosssectional age-earnings profiles to coincide with the life-cycle ones. In Figure3, we reproduce the cross-sectional profiles from Figure1on the left, and plot the life-cycle earnings path of various birth cohorts on the right, with each curve representing a10-year cohort bin. The top panel is for the U.S., and the bottom panel for China. In the U.S. (Figure3a), cohorts with year of birth expanding half a century share remarkably similar life-cycle earnings paths. Furthermore, life-cycle profiles on the right of Figure3a closely resemble the cross-sectional profiles on the left (which is reproduced from the right panel of Figure1a), in both its shape and level. In a stationary environment where the life-cycle profile does not vary across cohorts, the cross-sectional profiles and the life-cycle profiles essentially coincide with each other. In such an economy, a30-year-old worker who wants to predict his (real) earnings10years later can simply take a look at the contemporary earnings of a40-year-old worker. This provides a justification for the voluminous prior literature that use cross-sectional profiles as approximations to life-cycle patterns. Although conceptually it is not correct to interpret crosssectional age-earnings profiles as life-cycle patterns, in practice they are close to each other for the U.S. case. In other words, stationarity is an reasonable assumption when studying the U.S. earnings profiles. However, as shown in Figure3b, the life-cycle patterns of different cohorts differ drasticallyfor China. More recent cohorts enjoy both much higher earnings and steeper life-cycle earnings growth. These life-cycle profiles also demonstrate no resemblance at all to the cross-sectional profiles, although they are actually linked to each other. Note that both the left and the right panels are just different ways to visualize the same underlying data.13It is perhaps not surprising that in a fast-growing economy such as China, stationarity is not a valid approximation…”

Cross Section versus Life Earnings Age-Earnings Profiles

“…To sum up, Figure2plots the evolution of the cross-sectional “golden ages” in the U.S. and China during1986-2012. For each country and each year, we run a kernel regression of log earnings on age to predict age-specific earnings, and obtain an estimated golden age in that year as the age achieving the maximal predicted earnings. Furthermore, we fit a linear time trend of the estimated golden age for each country. Figure2shows clearly that in the U.S., the golden age has stayed constant at around48years old in the past thirty years, while in China there exhibits a strong downward trend in the golden ages from1986to2012, decreasing from more than55years old to around35years old….”

PRC, “…In Figure1b, we plot the cross-sectional age-earnings profile for Chinese male workers, using the same procedure as discussed before. There are several striking contrasts between Figure1a and Figure1b. First, Chinese workers have experienced a dramatic increase in real earnings in the past30years for all age groups. It is reflected in the large vertical upward shifts of the ageearnings profiles for later cross sections. The earnings of Chinese urban male workers increased by nearly six folds. This is in marked contrast to the earnings stagnation in the U.S. Second, while the shape of the cross-sectional age-earnings profiles and hence the corresponding “golden ages” have stayed more or less constant in the U.S., the “golden age” in China is continuously evolving to younger ages. Prior to2000, the age-earnings profiles of China had a familiar hump-shape with the “golden age” at around55, although there already were some signs of a declining “golden age” in1996-2000. Between2001and2004, the age-earnings profile is almost flat and humps at around age40-45. After2005, the “golden age” is35years old…”

US, “…Figure1a depicts the cross-sectional age-earnings profiles for male workers in the U.S. Each curve represents a cross section that pools five or four adjacent years. In the construction of each curve, we first perform a nonparametric kernel regression of annual labor earnings on age separately for each cross section, where the Epanechnikov kernel function and rule-of-thumb bandwidth estimator are applied, and then display the smoothed values with the95% confidence intervals. To avoid potential impacts of extreme values, we drop outliers defined as earnings in the top2.5% and bottom2.5% in each year. We normalize all earnings to the2015year using CPI. Individuals are weighted by the person-level ASEC weight. Figure1a reveals that, first, the “golden age” in the U.S. is relatively stable at around50years old during the past three decades;second, the U.S. has witnessed little growth in age-specific mean real earnings. That is, both the shape and the level of the age-earnings profiles are largely unchanged…”

The Evidence

Gregor Macdonald, “…The US has a much higher share of low-paying jobs than the rest of the OECD, potentially complicating the country’s efforts to pursue greater public investment. The observation comes from economist Jens Nordvig, of Exante Data. According to the OECD, nearly 24% of total jobs in the US are low paying, against an OECD average of 15.3%.That means long-timeline infrastructure projects may be challenged to find enough skilled labor, given that the US is carrying such a large load of unskilled jobs—mostly in food services. Looked at another way, however, this is precisely why the US should pursue broad, long term public investment programs. These are far more typical in the rest of the OECD, and undoubtedly account for part of the wage differentials. To put this bluntly, the US is overinvested in fast food production, and the strip mall economy more generally. Wage growth can never emanate from that segment of the economy, because it produces few useful increases in productivity. By contrast, cleaning out the pipes, so to speak, in the US water, transit, educational, and grid systems would justifiably throw off better wages as these efforts would lead to far better productivity and efficiency. America is discovering right now that workers are not keen to return to line-cook jobs at national burger chains. Maybe, just maybe, there’s a real signal there, worthy of our attention.To see a dynamic version of the chart below, just click on it….”

Work Matters

Oil prices remain quite firm, even as the international agencies gently dial back their demand forecasts. The price strength makes sense however, especially as we turn to the second half of the year. Travel is likely to accelerate, industrial applications will also strengthen, and commuting will be resurrected this autumn. The crude oil futures market cannot afford to misprice Q4, which is historically quite strong.

All this said, global demand is not on course (this year, at least) to match the 2019 highs around 100 mbpd. Thus, we are once again facing an oil market that’s challenging to describe. It requires some flexibility to understand that global re-openings means a fast demand recovery, while at the same time absorbing the likelihood that demand has finally peaked. More challenging still: envisioning a demand landscape that carries onward for years, oscillating around a flatline.

As far as the EIA is concerned, US petrol demand has indeed peaked. They said so once again in their recent STEO report. Next year’s demand will still not reach the 2019 highs. Indeed, US road fuel demand peaked years ago. But note the echo: while it will never sustainably rise again, it’s only fallen a little.

Two factors bear watching for 2022. First, the global economy is likely to be quite strong next year as it gathers momentum. This will of course put additional upward pressure on oil demand. Indeed, the IEA—which has held its 2021 demand recovery forecast to a bounce of 5.4 mbpd—now sees 2022 total demand matching the 2019 high near/at 100 mbpd. But strength in the economy will also mean the EV adoption curve will accelerate, avoiding (for the first time perhaps on a global basis) a significant percentage of ICE vehicles that would otherwise have hit the road.

The second factor will come through workplace and commuting changes, which are now likely to be sustained. Here, we should probably “fade” the idea that everyone will be offered new home or office flexibility. The percentage of workers and employers that go the distance on new workplace schedules is likely to be small. But it’s not zero.

A just published paper from the University of Chicago, for example, showed that hours expended by workers during last year’s work-from-home phase actually increased, while productivity decreased. At first glance, this would appear to spell doom for WFH prospects—until you look into the details. Productivity losses were weighted heavily towards those workers with children, while single workers fared better. One conclusion is obvious: children will be back at school fully in the years ahead, so any understandable productivity loss from having children at home will ameliorate. Work from home is a concept that’s now out in the open, and will not be put back so easily.

When Facebook announced last week it would be extending workplace flexibility to all employees, that was probably the loudest signal yet that WFH options are here to stay. As we learned during the pandemic, many global workers today wake at home, travel a long distance to work, only to sit down again in front of a computer terminal. Moreover, we have decades of data showing that commuting itself is a deadening experience that often interweaves itself into overall job dissatisfaction. WFH, even on a marginal basis, promises to change these dynamics for the better. But more important still, future WFH represents another sizable hit to global oil demand, helping to kill off another pathway to growth, and the risk that global demand exceeds the 2019 peak for any length of time.

The drought in the western United States has probably been going on for twenty years, and may actually be a mega-drought, comparable to one last seen over 500 years ago. That’s the conclusion of a study released last year, which used 1200 years of tree-ring data. More sobering: droughts build strength over time, making them harder to break out of, or terminate. One immediate concern is how much the west depends on hydropower. As other analysts have noted, rising temperatures, dry conditions, and falling water levels tend to drive responses that include greater use of air conditioning, and greater demand for power—which often leads to rising natural gas consumption. The past several years have also seen fire and smoke events that have blanketed large areas, not just in California, but Oregon and Washington. And not just for a day or two, but for weeks. The New York Times also covered the story this week. Here’s a graphic from their piece.

To see a dynamic version of the chart below, just click on it.

The real news however is the market share growth of NEV, now coming into clearer view. As we have observed, the 5% level tends to be a take-off point in the adoption of myriad technologies and in 2020 NEV finally notched a 5.4% share, after stalling around 4.6% the two years prior. Now, with the total Chinese vehicle market on pace to sell about 26 million units in 2021, NEV are on course to hit an 8.8% share of the market. Thus, NEV have now reached their overt tipping point, just as they’ve done in the California market, and the European market.

In the chart below, note the figures for ICE sales: down over 4 million units since the highs of 2017.

Lordstown Motors burned through a lot of cash, and has now warned it may not endure as a going concern. Investors should have been savvy enough to pick through last year’s oeur d'oeuvres tray of SPACs, choosing only those names that had earnings or sufficient capital. Chargepoint (CHPT) and STEM (STEM) are two examples of post-SPAC companies moving forward now with solid growth. Nikola (NKLA) and Lordstown (RIDE) offer the opposing case. It is frankly amazing that NKLA still trades above pennies per share. Lordstown, meanwhile, is discovering how difficult it can be to undertake a hardware start-up. Most embarrassing is that within a 60 day period, Lordstown provided radically different updates to investors on its cash position. Current status: “we don’t have enough capital to start producing.”

Bloomberg NEF released its global EV outlook, and raised its EV adoption guidance by the largest amount in five years. BNEF now sees global EV passenger cars rising from their 4% market share in 2020 (3.1 million units), to a 16% market share by 2025 (14 million units). Well, that’s a quadrupling of market share and a nearly 5X advance of units sold. Not bad. BNEF notes that divergences will be large, of course, between regions and picks China and Europe as market leaders—at least until 2025.

For a fleet perspective, which aggregates on-road EV, BNEF helpfully lays out that over 50 million passenger cars, and nearly 6 million EV buses and commercial vehicles, will be on-road by 2025. On an absolute basis, however, what’s quite astounding are the millions of two and three wheeled EV due to accumulate in the years ahead. The world will have added nearly another 75 million of these vehicle types by 2025. That represents a very large hit to oil growth, indeed. | Electric Vehicle Outlook 2021.

After falling 11% in 2020 energy related emissions will recover by about 6% this year, according to the EIA’s latest forecast. As for next year, EIA estimates emissions will advance by another 2%. This won’t take emissions back to the 2019 highs, but the recovery is fairly strong. The last few years have seen reasonably good progress but rapid closures of coal fired power plants and the plateau in US road fuel demand have mostly accounted for the emissions decline. The challenge now, however, is to put together fresh new blocks of decarbonization. As The Gregor Letter has pointed out, the US is simply not going to open up fresh decarb gains unless it does something more forceful about the existing auto fleet. | The chart below is complete through 2020.

Philipp Boeing and Paul Hünermundd, "A global decline in research productivity? Evidence from China and Germany,"Economics Letters, December 2020, https://www.sciencedirect.com/science/article/abs/pii/S0165176520304067

Chart

Editorial Board, "Where You Want to Get Cancer,"Wall Street Journal, January 9, 2020, https://www.wsj.com/articles/where-you-want-to-get-cancer-11578615274

Where You Want to Get Cancer

Cheer up, folks. For all the political grousing about health-care costs, the good news out this week is that cancer survival rates have improved enormously over the last three decades. The chances of beating most types of cancer are increasing, and that’s especially true if you live in the United States.

The American Cancer Society reported this week that the cancer mortality rate in the U.S. has plunged nearly 30% since its peak in 1991, with the biggest annual decline occurring in 2017. Fewer Americans are smoking, which has reduced the incidence of lung cancer in particular. More Americans are also being diagnosed with cancer at earlier stages thanks to better tests and screening, increasing the odds of survival.

The five-year survival rate is now 98% for prostate cancer, 92% for melanoma and 90% for breast cancer. Between 2013 and 2017, the death rate for men with melanoma declined by a stunning 7.6% annually. Screening and treatment improvements also helped reduce the death rate for breast cancer by an average of 1.5% annually from 2008 to 2017.

Scientific understanding of cancer and its genetic determinants has advanced by leaps over the past decade. Personal DNA testing companies like 23andMe arm people with more information about their risk factors. Most women now know, for example, that mutations in the BRCA1 and BRCA2 genes increase the risk for breast and ovarian cancers.

Breakthrough therapies that harness a victim’s immune system have also increased survival rates by multiples over traditional treatments such as chemotherapy. That’s especially true for cancers with low survival rates such as metastatic melanoma and lung cancer.

Such government rationing and price controls on drugs are one major reason that countries with socialized medicine like the United Kingdom have lower cancer survival rates than the U.S. The age-adjusted cancer mortality rate is about 20% higher in the U.K and 10% higher in Canada and France than in the U.S. Survival rates for hard-to-treat cancers are also higher in the U.S. than in most countries with nationalized health systems.

According to a study in the journal Lancet last year, an individual diagnosed with pancreatic cancer between 2010 and 2014 had nearly twice the likelihood of surviving five years in the U.S. than in the U.K. The five-year survival rate for brain cancer in the U.S. is 36.5% compared to 27.2% in France and 26.3% in the U.K. For stomach cancer the five-year survival rate is 33.1% in the U.S. compared to 26.7% in France and 20.7% in the U.K.

Diagnostic and treatment advances in the U.S. are also accelerating. Google’s artificial intelligence can now detect breast and lung cancers with better accuracy—meaning fewer false positives and negatives—than radiologists. AI systems are also enabling researchers to identify more genetic links and to personalize treatments.

Even the report’s gloomiest news has a silver lining. Death rates for liver cancer are rising faster than for other forms of the disease, but Hepatitis C drugs could greatly reduce the incidence and have come down 80% in price since 2014. It’s also worth highlighting that the disparity in cancer death rates between blacks and whites declined to 13% in 2017 from a peak of 33% in 1993.

Almost everyone knows someone who has been struck with cancer, and many have had bouts of their own. The good news is that the prognosis has never been better, and innovative drug therapies are a major reason.

Sailer updated his PISA by race category, US White (7th overall) and US Asians (3rd overall) do very well, US blacks and Hispanics not so much.

Editorial Board, "The Middle Class Always Pays," Wall Street Journal, November 28, 2019, https://www.wsj.com/articles/the-middle-class-always-pays-11574967052

“…Calculating how all this affects different income groups combines analysis of tax rates with consumption patterns and the like. Where economists have crunched the numbers, the result is grim for the middle class. Researchers at the DIW think tank in Berlin looked at Germany’s tax system in 2017 and found that median earners pay roughly the same proportion of income in taxes as the highest earners do—43%. Germans in the 60th and 70th percentiles of income pay a higher proportion of earnings in taxes than anyone else, approaching 52%.The wealthiest paid more tax on income and investment, but consumption and payroll taxes walloped the middle class. This is how Berlin balances its budget. American voters, beware. Politicians promising that Medicare for All and a Green New Deal can be financed by the rich are lying to you. The middle class will pay because that’s where the real money is….”

Europe shows how the Warren-Sanders agenda really works.

Most European nations have larger welfare and entitlement states than the U.S., though they spend less on defense. According to the Organization for Economic Cooperation and Development, government spending as a share of GDP ranges from about 56% in France to 44% in Germany and 41% in Britain.

The U.S. share of about 40% is financed largely by income taxes on the affluent and the payroll tax that funds Social Security and Medicare, plus state and local taxes and borrowing. Europe has learned the hard way that the rich aren’t rich enough to pay for their entitlements, so the Continent duns the middle class.

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Start with the income tax. Most European governments tax most household income more heavily than Washington does because they impose their highest marginal rates on lower levels of income. Germany’s second-highest marginal income-tax rate of 42% kicks in for married households earning around €112,000 ($124,000). An American couple with that income pays a marginal rate of only 22% and would need to earn $612,350 before paying the top marginal rate of 37%.

Sweden’s top marginal income-tax rate of about 55% applies to earnings as low as $47,000, and in the U.K. the second-highest rate of 40% hits taxpayers earning £50,000 ($64,000). By this standard America’s income tax is highly progressive. The U.S. top marginal rate applies only to taxpayers whose wages are 9.3 times the average wage. In Belgium the top marginal rate ensnares workers earning 1.1 times the average, and in the Netherlands 1.4 times.

The income tax isn’t enough to finance Europe’s vast welfare states, so governments also impose payroll taxes they describe as “social insurance contributions.” For a single American earning the average wage, the employer and employee payroll taxes for Social Security and Medicare average 16% of gross labor costs, according to the OECD.

In Britain the share for similar social-benefit payroll taxes is a little over 20%, and in Sweden and Germany about 40%. Such middle-class payroll taxes account for 35% of government revenue in Spain, 30% in Italy, and 37% in France and Germany, and without them Europe’s welfare systems would be bankrupt.

Elizabeth Warren has figured this out. Her Medicare for All plan includes an expanded payroll tax for employers that she says isn’t a tax on the middle class, but Europeans know better. Employer payroll taxes for social insurance account for as much as 25% of revenue in France or 20% in Belgium. This is a hidden tax on the middle class because it reduces the cash employers can offer in salaries.

Europe also imposes a value-added tax (VAT) with a flat rate averaging 21% on almost all consumption. These taxes account for up to a quarter of total government revenue in many countries. They’re regressive since lower-income households devote a larger share of income to consumption taxed by a VAT.

There are other middle-class revenue grabs. Excise taxation, including on fuel, accounts for 3% of total revenue in the U.S., but above 7% in Britain and 6.4% in Italy. As last year’s yellow-vest protests showed in France (where fuel and other excise taxes account for nearly 6% of annual revenue), this burden is more onerous for middle-class suburbanites and tradesmen than on the Ferrari-driving 0.1%.

Britain also soaks its middle class with a stamp tax on property purchases, amounting to about 1% of the price for the median home nationwide, and up to 3% for the median home in London. This discourages property transactions, making it harder for older middle-class households to cash out of their home equity while raising a barrier for the younger middle class to climb onto the property ladder.

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Calculating how all this affects different income groups combines analysis of tax rates with consumption patterns and the like. Where economists have crunched the numbers, the result is grim for the middle class.

Researchers at the DIW think tank in Berlin looked at Germany’s tax system in 2017 and found that median earners pay roughly the same proportion of income in taxes as the highest earners do—43%. Germans in the 60th and 70th percentiles of income pay a higher proportion of earnings in taxes than anyone else, approaching 52%. The wealthiest paid more tax on income and investment, but consumption and payroll taxes walloped the middle class. This is how Berlin balances its budget.

American voters, beware. Politicians promising that Medicare for All and a Green New Deal can be financed by the rich are lying to you. The middle class will pay because that’s where the real money is.